[2603.03258] Inherited Goal Drift: Contextual Pressure Can Undermine Agentic Goals

Computer Science > Artificial Intelligence arXiv:2603.03258 (cs) [Submitted on 3 Mar 2026] Title:Inherited Goal Drift: Contextual Pressure Can Undermine Agentic Goals Authors:Achyutha Menon, Magnus Saebo, Tyler Crosse, Spencer Gibson, Eyon Jang, Diogo Cruz View a PDF of the paper titled Inherited Goal Drift: Contextual Pressure Can Undermine Agentic Goals, by Achyutha Menon and 5 other authors View PDF HTML (experimental) Abstract:The accelerating adoption of language models (LMs) as agents for deployment in long-context tasks motivates a thorough understanding of goal drift: agents' tendency to deviate from an original objective. While prior-generation language model agents have been shown to be susceptible to drift, the extent to which drift affects more recent models remains unclear. In this work, we provide an updated characterization of the extent and causes of goal drift. We investigate drift in state-of-the-art models within a simulated stock-trading environment (Arike et al., 2025). These models are largely shown to be robust even when subjected to adversarial pressure. We show, however, that this robustness is brittle: across multiple settings, the same models often inherit drift when conditioned on prefilled trajectories from weaker agents. The extent of conditioning-induced drift varies significantly by model family, with only GPT-5.1 maintaining consistent resilience among tested models. We find that drift behavior is inconsistent between prompt variations and ...